Physical Layer Secret Key Generation and Coverage Enhancement for Time Variant UAV Wireless Communications

L Y Zhang, Weijie Tan, Qiangqiang Gao +1 more

Chenxi Liu, Rui Ma, Jemin Lee +1 more

Unmanned aerial vehicle (UAV) wireless communication has been considered to be a promising solution to provide ubiquitous coverage and enhanced capacity performance in the sixth-generation (6G) wireless networks. Against this background, safeguarding the UAV networks using physical layer security (PLS) techniques has been attracting significant research attention. In this chapter, we provide a comprehensive overview of PLS techniques in the UAV networks. Open problems and opportunities for PLS in the UAV networks are discussed. In addition, we take a UAV wiretap channel as an example and demonstrate how the design of the secure transmission scheme can effectively improve the secrecy performance of the considered UAV wiretap channel.

Yizhuo Wang, Qinghe Du, Ning Shen +3 more

With the rapid advancement of unmanned aerial vehicle (UAV), ensuring the security of communication links among UAVs has become crucial. In this paper, we propose a novel physical layer key generation scheme based on channel codeword reconstruction. In UAV communications, the high mobility of aerial nodes leads to short channel coherence time, which together with noise causes inevitable channel estimation errors. These errors significantly degrades the performance of wireless channel-based key generation. Therefore, we propose a codeword construction algorithm that achieves a polarization characteristic, which effectively segregates reliable keys from unreliable ones. Compared to the existing quantization-based key generation scheme, our approach maximize the utilization of raw channel information and employ soft-decision decoding to generate key. Simulation results demonstrate that the proposed scheme reduces the key disagreement rate for legitimate users and increases the number of consistently generated keys. Furthermore, our method ensures a lower key consistency rate for eavesdropper, which guarantees system security.

Meng Hua, Chunguo Li, Luxi Yang

Girish A. Koche, Amit Agarwal

Asim Ul Haq, Parwinder Singh, Albena Mihovska +1 more

Securing the communications link in reconfigurable intelligent surfaces (RISs) near-field (NF) wireless communications presents challenges, especially when uncrewed aerial vehicles (UAVs) provide the wireless communication links. NF communications have emerged as a pivotal area in next-generation wireless systems due to their focus on the spherical nature of waves and enhancing energy efficiency. They considered the best solution for consumer electronics, as the associated NF waves necessitate less energy for transmission in contrast to the planar waves employed in far-field communications. In the context of RIS, NF is critical since, in the far-field, a considerable portion of planar waves passes through the surface elements. Consequently, with UAV assistance, employing RIS in the NF effectively addresses the dynamic characteristics and reliability of communication links. However, the complexity of UAV and RIS models poses significant challenges for secure communication. This paper proposes two secret key generation (SKG) methods to address these challenges and secure RIS-connected users. The convergence of NF and RIS with physical layer-based SKG methods supported by UAV feed links has been analyzed in detail. An information reconciliation method to minimize key mismatch probability (KMP) has been further studied. The simulation results of the proposed methods demonstrate substantial improvements in securing NF-RIS communications within the UAV ecosystem.